Dear Colleagues,

 
a parallel session within the AMASES Annual Conference (https://www.amases.org/annual-conference-2021-home/) entitled "Networks, Big Data, and Artificial Intelligence in Economics, Finance, and Social Sciences" will take place on September 15, 2021 in virtual mode using the Zoom platform.
 
The session focuses on the emerging multidisciplinary study of the interconnections in finance and social science, which brings with it the necessity to deal with the growing amount of data available. A special emphasis is given to the latest advances in artificial intelligence and machine learning, which are expected to have a disruptive impact in economic, financial, and social data modeling. The stream intends to foster the dialogue between academics, regulators, and practitioners.

Theoretical and empirical papers are welcome. Topics include but are not limited to:

- contagion in social, economic, and financial networks

- network modeling of financial time-series

- big data approach to financial, economic, and social modeling

- artificial intelligence and machine learning in social, economic, and financial systems

 
It is a great pleasure to invite you to submit an extended abstract. The deadline for submission is August 31st, 2021. The abstract submission Web page for AMASES 2021 is: https://easychair.org/conferences/?conf=amases2021

As specified in the guidelines for abstract submission of the AMASES conference (please see https://www.amases.org/annual-conference-2021-abstract/), the title of the session and the name of the organizers have to be provided at the end of the abstract itself. Moreover, please also send a pdf copy of the abstract to the organizers of this parallel session (see below for the email address).

Please refer to the official web page of the conference for further details on the submission.

Important dates:

August 31, 2021: deadline for abstract submission

September 6, 2021: notification of acceptance

September 15, 2021: parallel session
 

For information, please contact:

Fabrizio Lillo (fabrizio.lillo@unibo.it)

Michele Tumminello (michele.tumminello@unipa.it)

Piero Mazzarisi (piero.mazzarisi@sns.it)

 
Best regards,

Fabrizio Lillo, Michele Tumminello, and Piero Mazzarisi